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PLANNING FOR AGENT CONTROL USING LEARNED HIDDEN STATES

机译:使用学习的隐藏状态规划代理控制

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting actions to be performed by an agent interacting with an environment to cause the agent to perform a task. One of the methods includes: receiving a current observation characterizing a current environment state of the environment; performing a plurality of planning iterations to generate plan data that indicates a respective value to performing the task of the agent performing each of the set of actions in the environment and starting from the current environment state, wherein performing each planning iteration comprises selecting a sequence of actions to be performed by the agent starting from the current environment state based on outputs generated by a dynamics model and a prediction model; and selecting, from the set of actions, an action to be performed by the agent in response to the current observation based on the plan data.
机译:方法,系统和设备,包括在计算机存储介质上编码的计算机程序,用于通过与环境交互的代理来选择要执行的动作以使代理执行任务。其中一个方法包括:接收特征在于环境的当前环境状态的当前观察;执行多个规划迭代以生成指示对执行环境中的每组动作的每个组的代理的任务的平面数据,并且从当前环境状态开始,其中执行每个规划迭代包括选择序列由基于动态模型生成的输出和预测模型的输出从当前环境状态开始执行的动作;从一组动作中选择由代理执行的动作响应于基于计划数据的当前观察来执行。

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